docs: def xminus1d(img, fun, dim, *args, **kwargs):
      r"""
      Applies the function fun along all X-1D dimensional volumes of the images img
      dimension dim.
      
      E.g. you want to apply a gauss filter to each slice of a 3D MRI brain image,
      simply supply the function as fun, the image as img and the dimension along which
      to iterate as dim.
      
      Parameters
      ----------
      img : ndarray
          The image to apply the function ``fun`` to.
      fun : function
          A image modification function.
      dim : integer
          The dimension along which to apply the function.
      
      Returns
      -------
      output : ndarray
          The result of the operation over the image ``img``.
      
      Notes
      -----
      With ``*args`` and ``**kwargs``, arguments can be passed to the function ``fun``.
      """
      slicer = [slice(None)] * img.ndim
      output = []
      for slid in range(img.shape[dim]):
          slicer[dim] = slice(slid, slid + 1)
          output.append(fun(numpy.squeeze(img[slicer]), *args, **kwargs))
      return numpy.rollaxis(numpy.asarray(output), 0, dim + 1)